Interested in this AI/ML Engineer role at Premera Blue Cross?
Apply Now →Skills & Technologies
About This Role
Workforce Classification:
Hybrid
Join Our Team: Do Meaningful Work and Improve People’s Lives
Our purpose, to improve customers’ lives by making healthcare work better, is far from ordinary. And so are our employees. Working at Premera means you have the opportunity to drive real change by transforming healthcare.
Premera is committed to being a workplace where people feel empowered to grow, innovate, and lead with purpose. By investing in our employees and fostering a culture of collaboration and continuous development, we’re able to better serve our customers. It’s this commitment that has earned us recognition as one of the best companies to work for. Learn more about our recent awards and recognitions as a greatest workplace.
Learn how Premera supports our members, customers and the communities that we serve through our Healthsource blog: https://healthsource.premera.com/ .
As a Solution Architect/AI Engineer IV , you will support the design, development, and implementation of sophisticated software and AI solutions. This position requires understanding of both software engineering principles and real\-world experience with AI implementation. In this role, you will operate in an agile team environment across different capability groups providing guidance on technical priorities, creating prototypes, and driving innovative solutions from concept to production.
This is a hybrid role located on our campus in Mountlake Terrace, Washington.
What you’ll do:
- Recommend and develop comprehensive systems and frameworks for AI applications and products, powering solutions for Digital Web experiences, strengths in managing additions for chatbot interfaces and backend services that support them, optimized for cost in consumption of tokens.
- Lead construction of prototypes and minimum viable products to validate AI solutions before committing substantial resources, expect to iterate fast and deliver such prototypes autonomously.
- Assist in designing and implementing the cloud architecture of large multi\-faceted AI systems.
- Develop specifications for low latency APIs and services necessary to deploy AI models and incorporate them into applications.
- Develop the code for monitoring models and AI systems that ensure consistent and reliable performance.
- Create and maintain thorough documentation that is consistent with team procedures, corporate policies, and expectations.
- Drive design reviews that align with our solution design process and actively participate in presenting and critical review of own and others designs.
- Guide other Solution Architects with industry best practices and methodologies, apply a similar approach when working with delivery teams, and provide critical input.
- Keep abreast of new tools and concepts constantly proving hypothesis in an experimentation environment.
- Advise team leadership on matters such as AI strategies with a focus on AI related technology strategies and roadmaps.
- Meet and collaborate with external stakeholders to conceptualize AI solutions that realize business value while ensuring AI governance adherence, AI best practices, data quality, reliability, and security.
What you’ll bring:
Required Qualifications
- Bachelor’s Degree in Computer Science, Information Systems, Statistics, Mathematics, or related field, or equivalent experience.
- Minimum of (12\) years of experience in software development and launching online customer products, with knowledge of the software development lifecycle and proficiency in multiple programming languages.
- At least (2\) years of industry experience in developing, deploying, and maintaining AI systems.
Preferred Qualifications
- Experience working with cloud solutions in a highly regulated environment. Experience in the healthcare industry is preferred.
- Experience working within agile\-like teams and environments, with exposure to API and service\-based technologies.
- Experience in successfully productionizing AI models, including constructing scalable data pipelines and establishing robust monitoring systems.
- Experience in using and creating automated test tools and a strong background in developing strategies for load testing AI experiences live in production.
- Knowledge of ethical AI practices include explainable AI, fairness, and bias mitigation.
Knowledge, Skills, and Abilities
- Expertise in implementing advanced techniques like Retrieval Augmented Generation, Tree of Thoughts, or Multimodal Chain of Thought in prompt engineering projects. Experience in leading prompt engineering teams and conducting code reviews.
- Proven experience debugging AI systems and enhancing performance through hyperparameter tuning and similar techniques.
- Knowledgeable about software design patterns, microservices, distributed computing, container orchestration, and other relevant architectures.
- Adept software engineering skills, as well as skills building secure, stable software systems at scale.
- Exceptional written and verbal communication skills, with the ability to articulate complex solutions to diverse stakeholders.
- Strong mentorship and leadership skills, with a commitment to knowledge sharing and professional development.
Physical Requirements
The following have been identified as essential physical requirements of this job and must be performed with or without accommodation:
- This is primarily a sedentary role which requires the ability to exert up to 10 lbs. of force occasionally and/or a negligible amount of force frequently or constantly to lift, carry, push, pull, or otherwise move objects, including the human body.
- This role requires the ability to keyboard and to communicate clearly and understandably in person and over the telephone.
Premera total rewards
Our comprehensive total rewards package provides support, resources, and opportunities to help employees thrive and grow. Our total rewards are more than a collection of perks, they're a reflection of our commitment to your health and well\-being. We offer a broad array of rewards including physical, financial, emotional, and community benefits, including:
- Medical, vision, and dental coverage with low employee premiums.
- Voluntary benefit offerings, including pet insurance for paw parents.
- Life and disability insurance.
- Retirement programs, including a 401K employer match and, believe it or not, a pension plan that is vested after 3 years of service.
- Wellness incentives with a wide range of mental well\-being resources for you and your dependents, including counseling services, stress management programs, and mindfulness programs, just to name a few.
- Generous paid time off to reenergize.
- Looking for continuing education? We have tuition assistance for both undergraduate and graduate degrees.
- Employee recognition program to celebrate anniversaries, team accomplishments, and more.
For our hybrid employees, our on\-campus model provides flexibility to create your own routine with access to on\-site resources, networking opportunities, and team engagement.
- Commuter perks make your trip to work less impactful on the environment and your wallet.
- Free convenient on\-site parking.
- Subsidized on\-campus cafes make lunchtime connections with colleagues fun and affordable.
- Participate in engaging on\-site activities such as health and wellness events, coffee connects, disaster preparedness fairs and more.
- Our complementary fitness \& well\-being center offers both in\-person and virtual workouts and nutritional counseling.
- Need a brain break? Challenge someone to a game of shuffleboard or ping pong while on campus.
Equal employment opportunity/affirmative action:
Premera is an equal opportunity/affirmative action employer. Premera seeks to attract and retain the most qualified individuals without regard to race, color, religion, sex, national origin, age, disability, marital status, veteran status, gender or gender identity, sexual orientation, genetic information or any other protected characteristic under applicable law.
If you need an accommodation to apply online for positions at Premera, please contact Premera Human Resources via email at [email protected] or via phone at 425\-918\-4785\.
The pay for this role will vary based on a range of factors including, but not limited to, a candidate’s geographic location, market conditions, and specific skills and experience.
The salary range for this role is posted below; we generally target up to and around the midpoint of the range.
National Plus Salary Range:
$150,300\.00 \- $270,500\.00
*\*National Plus salary range is used in higher cost of labor markets including Western Washington and Alaska* *.*
We’re happy to discuss compensation further during the interview because we believe that open communication leads to better outcomes for all. We’re committed to creating an environment where all employees are celebrated for their unique skills and contributions.
Salary Context
This $150K-$270K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Premera Blue Cross, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. Disclosed range: $150K to $270K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Premera Blue Cross AI Hiring
Premera Blue Cross has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Mountlake Terrace, WA, US. Compensation range: $270K - $270K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.